CPython Internals

A deep read of CPython: architecture, object model, memory management, compilation pipeline, and the evaluation loop.

10 items

Deep Reads › CPython Internals ›

1. Orientation

What CPython is, building from source, the repository layout, reading C code, the runtime model, and the path from source code to execution.
cpython python internals
Deep Reads › CPython Internals ›

2. Objects and Memory

The Python object model, PyObject and PyVarObject layout, reference counting, the garbage collector, memory allocators, and built-in type implementations.
cpython python internals
Deep Reads › CPython Internals ›

3. Compilation Pipeline

Tokenization, parsing, the AST, symbol tables, compiler passes, code objects, constants and locals, bytecode generation, and bytecode optimization.
cpython python internals
Deep Reads › CPython Internals ›

4. The Interpreter

The evaluation loop, frames, stack-based execution, bytecode instructions, function and method calls, attribute lookup, exceptions, generators, coroutines, pattern matching, comprehensions, and closures.
cpython python internals
Deep Reads › CPython Internals ›

5. Runtime Systems

Modules and imports, packages, the import lock, descriptors, classes and metaclasses, the MRO, the GIL, threads, subinterpreters, signals, context variables, and audit hooks.
cpython python internals
Deep Reads › CPython Internals ›

6. Standard Library Interfaces to the Core

How sys, inspect, dis, gc, types, importlib, ctypes, multiprocessing, and asyncio bridge Python code to CPython internals.
cpython python internals
Deep Reads › CPython Internals ›

7. C API and Extensions

The Python C API, reference ownership rules, creating extension modules, defining new types, the buffer protocol, capsules, stable ABI, limited API, embedding Python, and cross-language calls.
cpython python internals
Deep Reads › CPython Internals ›

8. Performance Internals

Interpreter dispatch, inline caches, the specializing adaptive interpreter, function call fast paths, vectorcall, dictionary and attribute access performance, memory locality, profiling, and benchmarking.
cpython python internals
Deep Reads › CPython Internals ›

9. Development Workflow

Running the test suite, debug builds, GDB and LLDB, sanitizers, tracing memory bugs, writing core tests, documentation, making patches, reading PEPs, and the release process.
cpython python internals
Deep Reads › CPython Internals ›

10. Advanced Topics

Free-threaded CPython, immortal objects, per-interpreter GIL, JIT work, stable ABI design tradeoffs, import system edge cases, serialization internals, security boundaries, and future directions.
cpython python internals